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Update README and index from chart release

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cbcoutinho
2025-11-09 06:22:17 +00:00
parent 939445166b
commit 88c2b2350d
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README.md
+157 -4
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@@ -14,8 +14,12 @@ This Helm chart deploys the Nextcloud MCP (Model Context Protocol) Server on a K
### Quick Start with Basic Authentication
```bash
# Add the Helm repository
helm repo add nextcloud-mcp https://cbcoutinho.github.io/nextcloud-mcp-server
helm repo update
# Install with basic auth (recommended for most users)
helm install nextcloud-mcp ./helm/nextcloud-mcp-server \
helm install nextcloud-mcp nextcloud-mcp/nextcloud-mcp-server \
--set nextcloud.host=https://cloud.example.com \
--set auth.basic.username=myuser \
--set auth.basic.password=mypassword
@@ -47,7 +51,7 @@ resources:
Install with your custom values:
```bash
helm install nextcloud-mcp ./helm/nextcloud-mcp-server -f custom-values.yaml
helm install nextcloud-mcp nextcloud-mcp/nextcloud-mcp-server -f custom-values.yaml
```
### OAuth Authentication Mode (Experimental)
@@ -202,6 +206,67 @@ The application exposes HTTP health check endpoints:
| `documentProcessing.unstructured.apiUrl` | Unstructured API URL | `http://unstructured:8000` |
| `documentProcessing.tesseract.enabled` | Enable Tesseract OCR | `false` |
#### Vector Search & Semantic Capabilities (Optional)
Enable semantic search capabilities by deploying a vector database (Qdrant) and embedding service (Ollama or OpenAI).
**Vector Sync Configuration:**
| Parameter | Description | Default |
|-----------|-------------|---------|
| `vectorSync.enabled` | Enable background vector synchronization | `false` |
| `vectorSync.scanInterval` | Scan interval in seconds | `3600` |
| `vectorSync.processorWorkers` | Number of concurrent processor workers | `3` |
| `vectorSync.queueMaxSize` | Maximum queue size for pending documents | `10000` |
**Qdrant Vector Database:**
Qdrant is deployed as a subchart when `qdrant.enabled` is `true`. All configuration values are passed through to the [qdrant/qdrant](https://github.com/qdrant/qdrant-helm) chart.
| Parameter | Description | Default |
|-----------|-------------|---------|
| `qdrant.enabled` | Deploy Qdrant as a subchart | `false` |
| `qdrant.replicaCount` | Number of Qdrant replicas | `1` |
| `qdrant.image.tag` | Qdrant version | `v1.12.5` |
| `qdrant.apiKey` | Optional API key for authentication | `""` |
| `qdrant.persistence.size` | Storage size for vector data | `10Gi` |
| `qdrant.persistence.storageClass` | Storage class | `""` |
| `qdrant.resources.requests.cpu` | CPU request | `200m` |
| `qdrant.resources.requests.memory` | Memory request | `512Mi` |
| `qdrant.resources.limits.cpu` | CPU limit | `1000m` |
| `qdrant.resources.limits.memory` | Memory limit | `2Gi` |
**Ollama Embedding Service:**
Ollama is deployed as a subchart when `ollama.enabled` is `true`. All configuration values are passed through to the [ollama/ollama](https://github.com/otwld/ollama-helm) chart. Alternatively, set `ollama.url` to use an external Ollama instance.
| Parameter | Description | Default |
|-----------|-------------|---------|
| `ollama.enabled` | Deploy Ollama as a subchart | `false` |
| `ollama.url` | External Ollama URL (use with `enabled: false`) | `""` |
| `ollama.embeddingModel` | Embedding model to use | `nomic-embed-text` |
| `ollama.verifySsl` | Verify SSL certificates | `true` |
| `ollama.replicaCount` | Number of Ollama replicas | `1` |
| `ollama.ollama.models.pull` | Models to pull on startup | `["nomic-embed-text"]` |
| `ollama.persistentVolume.enabled` | Enable persistent storage | `true` |
| `ollama.persistentVolume.size` | Storage size for models | `20Gi` |
| `ollama.resources.requests.cpu` | CPU request | `500m` |
| `ollama.resources.requests.memory` | Memory request | `1Gi` |
| `ollama.resources.limits.cpu` | CPU limit | `2000m` |
| `ollama.resources.limits.memory` | Memory limit | `4Gi` |
**OpenAI Embedding Provider (Alternative):**
Use OpenAI or any OpenAI-compatible API instead of Ollama.
| Parameter | Description | Default |
|-----------|-------------|---------|
| `openai.enabled` | Enable OpenAI embedding provider | `false` |
| `openai.apiKey` | OpenAI API key | `""` |
| `openai.existingSecret` | Use existing secret for API key | `""` |
| `openai.secretKey` | Key in secret containing API key | `api-key` |
| `openai.baseUrl` | Custom API endpoint (optional) | `""` |
## Examples
### Example 1: Basic Auth with Ingress
@@ -379,18 +444,106 @@ affinity:
topologyKey: kubernetes.io/hostname
```
### Example 5: Semantic Search with Qdrant and Ollama
Deploy with vector search capabilities using embedded Qdrant and Ollama:
```yaml
nextcloud:
host: https://cloud.example.com
auth:
mode: basic
basic:
username: admin
password: secure-password
# Enable vector sync
vectorSync:
enabled: true
scanInterval: 1800 # Scan every 30 minutes
processorWorkers: 5
# Deploy Qdrant as a subchart
qdrant:
enabled: true
persistence:
size: 20Gi
storageClass: fast-ssd
resources:
requests:
cpu: 500m
memory: 1Gi
limits:
cpu: 2000m
memory: 4Gi
# Deploy Ollama as a subchart
ollama:
enabled: true
embeddingModel: nomic-embed-text
persistentVolume:
size: 30Gi
storageClass: standard
resources:
requests:
cpu: 1000m
memory: 2Gi
limits:
cpu: 4000m
memory: 8Gi
```
Or use an external Ollama instance:
```yaml
vectorSync:
enabled: true
qdrant:
enabled: true
# Use external Ollama instead of deploying subchart
ollama:
enabled: false
url: "http://ollama.ai-services.svc.cluster.local:11434"
embeddingModel: nomic-embed-text
```
Or use OpenAI for embeddings:
```yaml
vectorSync:
enabled: true
qdrant:
enabled: true
# Use OpenAI instead of Ollama
openai:
enabled: true
apiKey: "sk-..."
# Or use existing secret:
# existingSecret: openai-api-key
# secretKey: api-key
```
## Upgrading
### To upgrade an existing deployment:
```bash
helm upgrade nextcloud-mcp ./helm/nextcloud-mcp-server -f custom-values.yaml
# Update the repository
helm repo update
# Upgrade with your custom values
helm upgrade nextcloud-mcp nextcloud-mcp/nextcloud-mcp-server -f custom-values.yaml
```
### To upgrade with new values:
```bash
helm upgrade nextcloud-mcp ./helm/nextcloud-mcp-server \
helm upgrade nextcloud-mcp nextcloud-mcp/nextcloud-mcp-server \
--set resources.limits.memory=1Gi
```
charts/nextcloud-mcp-server/README.md
+157 -4
View File
@@ -14,8 +14,12 @@ This Helm chart deploys the Nextcloud MCP (Model Context Protocol) Server on a K
### Quick Start with Basic Authentication
```bash
# Add the Helm repository
helm repo add nextcloud-mcp https://cbcoutinho.github.io/nextcloud-mcp-server
helm repo update
# Install with basic auth (recommended for most users)
helm install nextcloud-mcp ./helm/nextcloud-mcp-server \
helm install nextcloud-mcp nextcloud-mcp/nextcloud-mcp-server \
--set nextcloud.host=https://cloud.example.com \
--set auth.basic.username=myuser \
--set auth.basic.password=mypassword
@@ -47,7 +51,7 @@ resources:
Install with your custom values:
```bash
helm install nextcloud-mcp ./helm/nextcloud-mcp-server -f custom-values.yaml
helm install nextcloud-mcp nextcloud-mcp/nextcloud-mcp-server -f custom-values.yaml
```
### OAuth Authentication Mode (Experimental)
@@ -202,6 +206,67 @@ The application exposes HTTP health check endpoints:
| `documentProcessing.unstructured.apiUrl` | Unstructured API URL | `http://unstructured:8000` |
| `documentProcessing.tesseract.enabled` | Enable Tesseract OCR | `false` |
#### Vector Search & Semantic Capabilities (Optional)
Enable semantic search capabilities by deploying a vector database (Qdrant) and embedding service (Ollama or OpenAI).
**Vector Sync Configuration:**
| Parameter | Description | Default |
|-----------|-------------|---------|
| `vectorSync.enabled` | Enable background vector synchronization | `false` |
| `vectorSync.scanInterval` | Scan interval in seconds | `3600` |
| `vectorSync.processorWorkers` | Number of concurrent processor workers | `3` |
| `vectorSync.queueMaxSize` | Maximum queue size for pending documents | `10000` |
**Qdrant Vector Database:**
Qdrant is deployed as a subchart when `qdrant.enabled` is `true`. All configuration values are passed through to the [qdrant/qdrant](https://github.com/qdrant/qdrant-helm) chart.
| Parameter | Description | Default |
|-----------|-------------|---------|
| `qdrant.enabled` | Deploy Qdrant as a subchart | `false` |
| `qdrant.replicaCount` | Number of Qdrant replicas | `1` |
| `qdrant.image.tag` | Qdrant version | `v1.12.5` |
| `qdrant.apiKey` | Optional API key for authentication | `""` |
| `qdrant.persistence.size` | Storage size for vector data | `10Gi` |
| `qdrant.persistence.storageClass` | Storage class | `""` |
| `qdrant.resources.requests.cpu` | CPU request | `200m` |
| `qdrant.resources.requests.memory` | Memory request | `512Mi` |
| `qdrant.resources.limits.cpu` | CPU limit | `1000m` |
| `qdrant.resources.limits.memory` | Memory limit | `2Gi` |
**Ollama Embedding Service:**
Ollama is deployed as a subchart when `ollama.enabled` is `true`. All configuration values are passed through to the [ollama/ollama](https://github.com/otwld/ollama-helm) chart. Alternatively, set `ollama.url` to use an external Ollama instance.
| Parameter | Description | Default |
|-----------|-------------|---------|
| `ollama.enabled` | Deploy Ollama as a subchart | `false` |
| `ollama.url` | External Ollama URL (use with `enabled: false`) | `""` |
| `ollama.embeddingModel` | Embedding model to use | `nomic-embed-text` |
| `ollama.verifySsl` | Verify SSL certificates | `true` |
| `ollama.replicaCount` | Number of Ollama replicas | `1` |
| `ollama.ollama.models.pull` | Models to pull on startup | `["nomic-embed-text"]` |
| `ollama.persistentVolume.enabled` | Enable persistent storage | `true` |
| `ollama.persistentVolume.size` | Storage size for models | `20Gi` |
| `ollama.resources.requests.cpu` | CPU request | `500m` |
| `ollama.resources.requests.memory` | Memory request | `1Gi` |
| `ollama.resources.limits.cpu` | CPU limit | `2000m` |
| `ollama.resources.limits.memory` | Memory limit | `4Gi` |
**OpenAI Embedding Provider (Alternative):**
Use OpenAI or any OpenAI-compatible API instead of Ollama.
| Parameter | Description | Default |
|-----------|-------------|---------|
| `openai.enabled` | Enable OpenAI embedding provider | `false` |
| `openai.apiKey` | OpenAI API key | `""` |
| `openai.existingSecret` | Use existing secret for API key | `""` |
| `openai.secretKey` | Key in secret containing API key | `api-key` |
| `openai.baseUrl` | Custom API endpoint (optional) | `""` |
## Examples
### Example 1: Basic Auth with Ingress
@@ -379,18 +444,106 @@ affinity:
topologyKey: kubernetes.io/hostname
```
### Example 5: Semantic Search with Qdrant and Ollama
Deploy with vector search capabilities using embedded Qdrant and Ollama:
```yaml
nextcloud:
host: https://cloud.example.com
auth:
mode: basic
basic:
username: admin
password: secure-password
# Enable vector sync
vectorSync:
enabled: true
scanInterval: 1800 # Scan every 30 minutes
processorWorkers: 5
# Deploy Qdrant as a subchart
qdrant:
enabled: true
persistence:
size: 20Gi
storageClass: fast-ssd
resources:
requests:
cpu: 500m
memory: 1Gi
limits:
cpu: 2000m
memory: 4Gi
# Deploy Ollama as a subchart
ollama:
enabled: true
embeddingModel: nomic-embed-text
persistentVolume:
size: 30Gi
storageClass: standard
resources:
requests:
cpu: 1000m
memory: 2Gi
limits:
cpu: 4000m
memory: 8Gi
```
Or use an external Ollama instance:
```yaml
vectorSync:
enabled: true
qdrant:
enabled: true
# Use external Ollama instead of deploying subchart
ollama:
enabled: false
url: "http://ollama.ai-services.svc.cluster.local:11434"
embeddingModel: nomic-embed-text
```
Or use OpenAI for embeddings:
```yaml
vectorSync:
enabled: true
qdrant:
enabled: true
# Use OpenAI instead of Ollama
openai:
enabled: true
apiKey: "sk-..."
# Or use existing secret:
# existingSecret: openai-api-key
# secretKey: api-key
```
## Upgrading
### To upgrade an existing deployment:
```bash
helm upgrade nextcloud-mcp ./helm/nextcloud-mcp-server -f custom-values.yaml
# Update the repository
helm repo update
# Upgrade with your custom values
helm upgrade nextcloud-mcp nextcloud-mcp/nextcloud-mcp-server -f custom-values.yaml
```
### To upgrade with new values:
```bash
helm upgrade nextcloud-mcp ./helm/nextcloud-mcp-server \
helm upgrade nextcloud-mcp nextcloud-mcp/nextcloud-mcp-server \
--set resources.limits.memory=1Gi
```